It is planned to expand the study for reducing parameter uncertainties based on satellite retrieved land surface temperature with several other observations.
Constraining a hydrological model with various data from different sources will lead to higher certainty for hydrologic predictions. In-situ observations of soil moisture and evapotranspiration are one potential source. These variables have major influence on the water balance and thus can be used to better constrain model parameters. New technologies like cosmic ray neutron sensing and soil moisture retrievals from ground truth stations of the Global Navigation Satellite System, are thrilling opportunities to strengthen the predictive power of hydrologic models.
Satellite retrieved soil moisture and evapotranspiration data unreliable in terms of accuracy and temporal continuity, yet. However, satellites deliver valuable infor-mation about the spatial and temporal distribution of the afore-mentioned vari-ables. Satellite earth observations are a promising source of reliable information in future. Hydrologic models should be ready to make use of this broadly available data resource. Approaches for calibrating mHM on soil moisture data are focus of my current research.
An additional promising data source is the Gravity Recovery and Climate Exper-iment (GRACE). GRACE observes the changes in the earth’s gravity field. These changes can be directly attributed to the total water storage, which describes the mass of the surface and subsurface water. Total water storage observations have already shown high potential to improve hydrologic predictions if considered in the parameter estimation process. Unfortunately, these data are very coarse in temporal (100-400 km) and spatial resolution (1 month).
So far, the German Drought Monitor is based on assessing the current state of the soil moisture in Germany. A seasonal forecasting system would be beneficial to planning purposes and mitigation measures. The most straightforward way to make seasonal drought forecasts is to design an Ensemble Streamflow Prediction system. This system uses past observations of meteorological variables, e.g., pre-cipitation, instead of a numerical weather forecasts. The future development of the monitor will focus on the implementation of an Ensemble Streamflow Prediction
6.2. Outlook system, while a subsequent development will aim on the integration of probabilistic numerical weather forecasts.
The need for the implementation of indices, e.g., Standardized Precipitation Index or Runoff Index, will be assessed during stakeholder consultations. Therefore, the Climate Office of Central Germany, seated at our department, aims to bring together natural and social scientists as well as decision makers and stakeholders.
This cooperation will determine additional requirements on the German Drought Monitor and will significantly influence its’s future appearance.
Summarizing, the implementation of the German Drought Monitor was a step forward for informing the public and decision makers about agricultural droughts.
The historic reconstruction of droughts enables the evaluation of ongoing events using benchmark drought events. Thus, potential negative impacts of drought events may be mitigated based on information delivered by the herein developed and published operational system.
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